Large scale networks typically comprise many client machines connected to a multi-tiered web of interconnected network elements (NEs). Typically, multiple redundant NEs are present to function as backup systems for each other. In the event that any one NE ceases to function properly, a redundant NE can quickly accept the failed NEs data traffic so that the network can continue to function normally.
Data traffic between client machines is typically routed through the network based solely on a cost algorithm. The cost algorithm may include a variety of metrics meant to represent system delay and reliability. A typical cost algorithm does not include any metric related to the power usage of the network. The result is that traditional cost-only routing ignores energy efficiency and may require a network to function in a manner that is grossly energy inefficient. For example, two data paths may be routed through two NEs even though one NE could handle both routes and allow the other NE to be placed in a hibernation mode. Due to the ever increasing cost of energy and the constant demand for increased communication bandwidth, the adoption of energy efficient processes may save telecommunication service providers from significant monetary waste.
Existing processes are incapable of gathering power consumption data for a network at different network states in a consistent and useful format. Without sufficient power consumption data for the network, intelligent routing decisions for increased energy efficiency cannot be made. Without consistent energy efficiency metrics, any new data paths are setup without regard to energy cost, and existing traffic cannot be transferred to more optimal data paths as system demands change.